The Long Tail model describes a business principle in which revenue comes less from individual bestsellers than from the aggregate of many niche products. In a classic distribution, a few top products generate most of the revenue. The Long Tail model inverts this logic: when storage and distribution costs are low enough, the mass of niche items can in total be more profitable than the hits.
Amazon is the prime example: a physical bookstore might carry 100,000 titles, Amazon millions. Titles beyond the top 100,000 sell individually rarely but in aggregate make up a considerable share of revenue. Netflix works similarly: the catalog contains thousands of titles that are individually low-demand but find their respective niche through algorithmic recommendations. Spotify turns millions of songs that would never play on radio into a viable business in aggregate.
The concept was described in 2006 by Chris Anderson. Prerequisites for a Long Tail model are low marginal costs per additional product and a capable search and recommendation system that guides customers to relevant niche products.